Tutorial: Take a data plot and make it better

Dianne Cook
Monash University

Session 2: Practice, polish and significance

Outline

time topic
15 Fixing the plot design
10 Guided exercises
15 Styling and theming
10 Guided exercises
15 Styling and theming
10 Guided exercises
20 Making YOUR plot better

Fixing the plot design

Example 1

What are the errors in this plot?

Variables are:

  • Number of TVs in household
  • Average math score
  • Country

We are examining the relationship between average math score and number of televisions in the household across 6 countries.

Perceiving trend is distracted by

  • different average values
  • ordering of countries

Reasonable aspects:

  • Aspect ratio for examining trend
  • Missing value category removed

Example 2

What are the problems with this plot?

Variables are: year, count, country

Mapping: x=year, y=count, colour=country

Message?

Compare change in TB incidence over time in different countries

Styling and theming

Styling

The BBC cookbook has good basic advice. The work of Amanda Cox has been instrumental in the NY Times data visualisations.


Elements that are important in plot design are many.

Remember:

  • The data should pops to be the pre-attentive element
  • Grids are important for lining up values with axis values
  • Mapping of data should be appropriate
  • Legends or callouts/annotations
  • Axis text: don’t repeat yourself (e.g. “%” or “000, 000” at each tick mark)
  • Aspect ratio: square, short and wide, tall and skinny
  • Colour choices and application
  • Titles for journalism but captions for science
  • Small multiples
  • Scales allow for comparison
  • Layering order
  • Information is meaningful to the intended audience

Example 1



How would you polish these plots?




Is the pattern visible and real

Making your own plot better

End of session 2

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